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Data Modelling Podcast – Chickens and Eggs, and Pots

By |2017-12-05T00:50:31+11:00November 7th, 2017|Podcast|

We now make available the second instalment of the DjangoModelling.com Data Modelling Podcast. This session talks about chickens and eggs in data modelling, and then discusses a simple example of data modelling.   A new podcast in the series will be released on the first Monday of each month (God willing).

Django and sub-classing (#54 – #56)

By |2017-11-14T17:17:57+11:00October 17th, 2017|Django, Modelling principles, Newsletter|

When modelling data, we often need to distinguish between different types of objects.  For example, a mapping application may need to store information about both roads and lakes, or a library catalogue may need to store data about both books and DVDs.  With these examples, the objects can be quite diverse and the details stored [...]

Data Modelling Podcast – Introduction

By |2017-10-03T00:25:30+11:00October 2nd, 2017|Podcast|

We now make available the inaugural DjangoModelling.com Data Modelling Podcast. This session talks about data modelling in the past and our reasons and methods for modelling data now.   A new podcast in the series will be released on the first Monday of each month (God willing).

Hardware hides performance pitfalls (#52)

By |2018-10-21T00:09:16+11:00September 21st, 2017|Modelling principles, Newsletter|

Data modelling is not the only limiter of performance. When I first started working with databases, performance in all aspects of computing was much worse than it is now.  However well an expert might craft a query, and however simple the query might be, technical restrictions would always limit the performance to just a few [...]

Missing data (#51)

By |2018-10-21T00:11:57+11:00September 11th, 2017|Modelling principles, Newsletter|

A very common problem with databases is missing data. Missing data makes searches difficult (or impossible) and statistics unreliable. Two common reasons for this are: Records contain optional fields which have been left empty. Records are completely missing because some of the mandatory information was not available. Since the missing data was in mandatory columns, [...]

Which RDBMS? (#50)

By |2018-10-21T00:16:30+11:00September 4th, 2017|Modelling principles, Newsletter|

In this series of newsletters, we concentrate on data modelling in general and discuss relational databases when we need to consider specific applications.  In general, we do not consider the so-called “NoSQL” databases.  Relational database management systems lend themselves to the use of fixed schemas and also provide easy type checking. […]

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